Applications of Prompt Engineering
Discover how utilizing prompts can boost capabilities and streamline workflows across various applications.
In NLP, prompts have become a flexible tool with many applications in various fields. Prompts allow users to direct the behavior and output of NLP models by giving them explicit instructions or signals, resulting in more precise and customized results. In this lesson, we look at how NLP prompts have transformed the ways we interact with and use language models.
Text generation and summarization#
In text generation, prompts serve as invaluable companions, offering a starting point as we venture into the realm of coherent and contextually appropriate text. By utilizing prompts, we can embark on the journey of crafting captivating content, be it through creating engaging stories, poems, or compelling product descriptions.
Additionally, prompts play a pivotal role in text summarization, allowing models to distill large volumes of data into concise and insightful summaries, saving time and effort for users.
An example of a prompt to generate a story is the following:
Prompt: Generate a captivating story about an unexpected adventure that starts with the following sentence: “On a quiet evening, as the sun dipped below the horizon, Tim received an intriguing message that would change his life forever.” |
Setting up the scene and introducing our main character encourages the model to generate a coherent and contextually appropriate story around an unexpected adventure.
Information retrieval#
We often encounter a vast expanse of textual data where we need to extract specific entities, facts, insights, or retrieve information to answer a question. Using targeted prompts, NLP models can effectively pinpoint and retrieve precise information.
Take an example of an e-commerce business that responds to customers’ inquiries about product specifications. To efficiently handle these inquiries and provide quick and accurate responses, we can employ an information retrieval system powered by prompts.
Prompt: Retrieve the key specifications of the [Latest Smartphone Model] and provide a concise and accurate response to a customer’s inquiry about the product. [Customer’s inquiry] |
Here, we retrieve specific information about the latest smartphone model that the customer is interested in.
Sentiment analysis and text classification#
Prompts play an important role in sentiment analysis and text classification. By providing explicit labels or categories in prompts, we can accurately classify textual data on the basis of sentiment (positive, neutral, negative) or into topics (politics, sports, technology, entertainment, and so on).
Consider a social media platform that monitors the sentiments of users towards different products. By using prompts, the platform can effectively classify the users’ comments into positive, neutral, or negative sentiments for each product.
Prompt: Classify the sentiment of the user comments below as positive, neutral, or negative using sentiment analysis techniques. Highlight the three most common pain points users face and the top three aspects where users find satisfaction. [Comments] |
Here, we can provide the users’ comments in a prompt and ask ChatGPT to classify these. Additionally, we inquire about the three most common challenges that users encounter, as well as the top three aspects that users find satisfying.
Language translation#
Language translation is yet another exciting and valuable feature of NLP models. By providing a source text together with the desired target language as a prompt, NLP models can generate high-quality translations. The advantage of using the NLP model compared to any other translator is the accuracy and contextually appropriate translations which goes beyond word-by-word conversion and captures the essence of the original text.
Prompt: Translate the following passage from English to French, ensuring the meaning and contextual nuances are accurately conveyed. [Passage] |
Code generation#
Code generation using prompts is a fascinating feature for individuals at all levels of programming proficiency. For people unfamiliar with programming, code generation allows them to communicate their requirements in simple language to the model. In return, the model provides the desired code that fulfills the requirements. This relieves individuals from the need to acquire in-depth knowledge of programming.
Even for seasoned programmers, code generation accelerates the workflow and allows them to focus more on high-level design instead of spending time on boilerplate code. Let’s look at an example of how to generate a simple addition function using ChatGPT.
Prompt: Write a Python program that asks the user to enter two numbers and calculates their sum. |
In addition to the aforementioned applications of prompt engineering, there are other noteworthy areas where it finds importance. These include question-answering, chatbot development, speech recognition, and more.
Within the scope of this course, we will make effective use of ChatGPT's information retrieval, text generation, and summarization capabilities to assist us in various aspects of solopreneurship. By incorporating these functionalities into our solopreneurship journey, we can harness the power of ChatGPT to streamline our research, content creation, and decision-making processes, enabling us to operate more efficiently and effectively as solopreneurs.
Practice#
We have learned some of the use cases of ChatGPT. It's now time to see it in action. Your task is to write a prompt instructing ChatGPT to write a poem on a topic of your choice and in the style of your favorite poet.
Write a poem on “Shining Stars” in the style of Emily Dickinson.
Fundamentals of Prompt Engineering
What is Market Research?